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Course Criteria
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3.00 Credits
Studies introductory statistics and probability, visual methods for summarizing quantitative information, basic experimental design and sampling methods, ethics and experimentation, causation, and interpretation of statistical analyzes. Applications use data drawn from current scientific and medical journals, newspaper articles, and the Internet. Students will not receive credit for both STAT 110 and STAT 112.
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3.00 Credits
Includes graphical displays of data, relationships in data, design of experiments, causation, random sampling, probability distributions, inference, confidence intervals, tests of hypotheses, and regression and correlation. Students will not receive credit for both STAT 110 and STAT 112. (IR) Credits: 3
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3.00 Credits
Statistics for Biology and Medicine Credits: 3
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3.00 Credits
This course includes a basic treatment of probability, and covers inference for one and two populations, including both hypothesis testing and confidence intervals. Analysis of variance and linear regression are also covered. Applications are drawn from biology and medicine.
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4.00 Credits
Introduction to the probability and statistical theory underlying the estimation of parameters and testing of statistical hypotheses, including those arising in the context of simple and multiple regression models. Students will use computers and statistical programs to analyze data. Examples and applications are drawn from economics, business, and other fields. Students will not receive credit for both STAT 212 and ECON 371.
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1.00 - 4.00 Credits
This course provides the opportunity to offer a new topic in teh subject area of statistics.
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3.00 Credits
Introduces statistical computing using S-PLUS. Topics include descriptive statistics for continuous and categorical variables, methods for handling missing data, basics of graphical perception, graphical displays, exploratory data analysis, and the simultaneous display of multiple variables. Students should be experienced with basic text-editing and file manipulation on either a PC or a UNIX system, and with either a programming language (e.g. BASIC) or a spreadsheet program (e.g. MINITAB or EXCEL). Credit earned in this course cannot be applied toward a graduate degree in statistics.
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3.00 Credits
Most elementary statistics courses start with a technique & present various surface level examples. This course will use relatively complicated data sets and approach them from multiple angles with elementary statistical techniques. Simulation techniques such as the bootstrap will also be used. Prerequisites: STAT 1100 or STAT 2020 or STAT 2120 or APMA 3110 or APMA 3120 or AP credit in Statistics.
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3.00 Credits
This course provides a calculus-based introduction to mathematical statistics with some applications. Topics include: sampling theory, point estimation, interval estimation, testing hypotheses, linear regression, correlation, analysis of variance, and categorical data. Recommended MATH 3100
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3.00 Credits
Discusses the main designs and estimation techniques used in sample surveys; including simple random sampling, stratification, cluster sampling, double sampling, post-stratification, and ratio estimation. Non-response problems and measurement errors are also discussed. Many properties of sample surveys are developed through simulation procedures. The SUDAAN software package for analyzing sample surveys is used.
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